Image Fusion for Travel Time Tomography Inversion

The travel time tomography technology had achieved wide application, the hinge of tomography was inversion algorithm, the ray path tracing technology had a great impact on the inversion results. In order to improve the SNR of inversion image, comprehensive utilization of inversion results with diffe...

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Main Authors: Liu Linan, Zhao Xiaomeng, Yin Xinghui, Ashraf Muhammad Aqeel
Format: Article
Language:English
Published: Sciendo 2015-09-01
Series:Polish Maritime Research
Subjects:
Online Access:https://doi.org/10.1515/pomr-2015-0047
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spelling doaj-6ad010bbe2ce4258a797f085792b36202021-09-05T13:59:48ZengSciendoPolish Maritime Research2083-74292015-09-0122s114915610.1515/pomr-2015-0047pomr-2015-0047Image Fusion for Travel Time Tomography InversionLiu Linan0Zhao Xiaomeng1Yin Xinghui2Ashraf Muhammad Aqeel3College of Computer and Information, Hohai University, Nanjing 210098, ChinaCollege of Information Engineering, Anhui Science and Technology University, Chuzhou 233100, ChinaCollege of Computer and Information, Hohai University, Nanjing 210098, ChinaDepartment of Geology, Faculty of Science, University Of Malaya 50603 Kuala Lumpur, MalaysiaThe travel time tomography technology had achieved wide application, the hinge of tomography was inversion algorithm, the ray path tracing technology had a great impact on the inversion results. In order to improve the SNR of inversion image, comprehensive utilization of inversion results with different ray tracing can be used. We presented an imaging fusion method based on improved Wilkinson iteration method. Firstly, the shortest path method and the linear travel time interpolation were used for forward calculation; then combined the improved Wilkinson iteration method with super relaxation precondition method to reduce the condition number of matrix and accelerate iterative speed, the precise integration method was used to solve the inverse matrix more precisely in tomography inversion process; finally, use wavelet transform for image fusion, obtain the final image. Therefore, the ill-conditioned linear equations were changed into iterative normal system through two times of treatment and using images with different forward algorithms for image fusion, it reduced the influence effect of measurement error on imaging. Simulation results showed that, this method can eliminate the artifacts in images effectively, it had extensive practical significance.https://doi.org/10.1515/pomr-2015-0047tomographyinversion algorithmwavelet transformimage fusion
collection DOAJ
language English
format Article
sources DOAJ
author Liu Linan
Zhao Xiaomeng
Yin Xinghui
Ashraf Muhammad Aqeel
spellingShingle Liu Linan
Zhao Xiaomeng
Yin Xinghui
Ashraf Muhammad Aqeel
Image Fusion for Travel Time Tomography Inversion
Polish Maritime Research
tomography
inversion algorithm
wavelet transform
image fusion
author_facet Liu Linan
Zhao Xiaomeng
Yin Xinghui
Ashraf Muhammad Aqeel
author_sort Liu Linan
title Image Fusion for Travel Time Tomography Inversion
title_short Image Fusion for Travel Time Tomography Inversion
title_full Image Fusion for Travel Time Tomography Inversion
title_fullStr Image Fusion for Travel Time Tomography Inversion
title_full_unstemmed Image Fusion for Travel Time Tomography Inversion
title_sort image fusion for travel time tomography inversion
publisher Sciendo
series Polish Maritime Research
issn 2083-7429
publishDate 2015-09-01
description The travel time tomography technology had achieved wide application, the hinge of tomography was inversion algorithm, the ray path tracing technology had a great impact on the inversion results. In order to improve the SNR of inversion image, comprehensive utilization of inversion results with different ray tracing can be used. We presented an imaging fusion method based on improved Wilkinson iteration method. Firstly, the shortest path method and the linear travel time interpolation were used for forward calculation; then combined the improved Wilkinson iteration method with super relaxation precondition method to reduce the condition number of matrix and accelerate iterative speed, the precise integration method was used to solve the inverse matrix more precisely in tomography inversion process; finally, use wavelet transform for image fusion, obtain the final image. Therefore, the ill-conditioned linear equations were changed into iterative normal system through two times of treatment and using images with different forward algorithms for image fusion, it reduced the influence effect of measurement error on imaging. Simulation results showed that, this method can eliminate the artifacts in images effectively, it had extensive practical significance.
topic tomography
inversion algorithm
wavelet transform
image fusion
url https://doi.org/10.1515/pomr-2015-0047
work_keys_str_mv AT liulinan imagefusionfortraveltimetomographyinversion
AT zhaoxiaomeng imagefusionfortraveltimetomographyinversion
AT yinxinghui imagefusionfortraveltimetomographyinversion
AT ashrafmuhammadaqeel imagefusionfortraveltimetomographyinversion
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